基于深度CNN的陆空通话语义一致性校验

中国民航大学学报

基于深度CNN的陆空通话语义一致性校验

杨金锋，卢薇冰，贾桂敏，师一华

（中国民航大学天津市智能信号与图像处理重点实验室，天津300300）

收稿日期:2017-03-15 修回日期:2017-04-14 出版日期:2018-02-24 发布日期:2018-01-17
作者简介:杨金锋（1971—），男，河南淮阳人，教授，工学博士，研究方向为图像处理、生物识别、计算机视觉.
基金资助:
国家自然科学基金项目（U1433120，61379102，61502498）；中央高校基本科硕业务费专项（3122017001）

Semantic consistency verification of radiotelephony communication based on deep CNN

YANG Jinfeng, LU Weibing, JIA Guimin, SHI Yihua

(Intelligent Signal and Image Processing Key Lab of Tianjin, CAUC, Tianjin 300300, China)

Received:2017-03-15 Revised:2017-04-14 Online:2018-02-24 Published:2018-01-17

摘要/Abstract

摘要： 陆空通话复诵的准确性对飞行安全有着重要作用。由于飞行员和管制员在复诵过程中会无意识地产生一些问题，提出利用深度卷积神经网络（deep CNN，deep convolutional neural network）方法对陆空通话内容的语义进行一致性校验。首先将陆空通话语料库中的词语进行词向量转化，在此基础上，利用CNN 得到飞行员和管制员复诵对的语义向量，然后利用余弦相似度对其语义相似性进行度量，最后通过分类器完成一致性校验。通过实验可证明，CNN 可有效地实现陆空通话语义一致性校验，且实验精度结果能够达到82.5%。

关键词: 陆空通话, 深度卷积神经网络, 语义一致性校验, 语义向量

Abstract: The accuracy of readback plays an important role in flight safety. However, readback semantic inconsistency may occurs during radiotelephony communication. Thus, a method based on deep CNN (convolutional neural network) is proposed to verify semantic consistency of readback content. Words in radiotelephony communication corpus are transformed into word vectors. On top of the word vectors, CNN model is used to obtain the semantic vectors of readback sentence pairs, then cosine measurement is applied to measure the semantic similarity of readback sentence pairs. Finally, consistency verification is implemented by classifier. Experiment results show that semantic consistency of radiotelephony communication can be verified by CNN model effectively. The average accuracy of the experiments is up to 82.5%.

Key words: radiotelephony communication, deep CNN, semantic consistency verification, semantic vector

中图分类号:

V355
TP391

杨金锋，卢薇冰，贾桂敏，师一华. 基于深度CNN的陆空通话语义一致性校验[J]. 中国民航大学学报.

YANG Jinfeng, LU Weibing, JIA Guimin, SHI Yihua. Semantic consistency verification of radiotelephony communication based on deep CNN[J]. .

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